A growing number of individuals use activity sensors, for example, to obtain information pertaining to their daily physical activity and performance. Activity sensors commonly capture data from user movements, provided by components such as accelerometers, gyroscopes, etc. Additionally, models can be used to correlate the captured data to a predefined set of movements. However, challenges existing using current approaches due to a lack of training examples and improper positioning of such sensors, which limits the ability to capture meaningful information about the user movements.